• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.05a
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• pp.251-252
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• 2023

As technology improves with the 4th industrial revolution, smart construction is becoming a key part of safety management in the architecture and civil engineering. By using object detection technology with CCTV data, construction sites can be managed efficiently. In this study, super resolution technology based on deep learning is proposed to improve the accuracy of object detection in construction sites. As the resolution of a train set data and test set data get higher, the accuracy of object detection model gets better. Therefore, according to the scale of construction sites, different object detection models can be considered.

• Parasites, Hosts and Diseases
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• v.54 no.3
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• pp.375-380
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• 2016

Angiostrongyliasis is difficult to be diagnosed for the reason that no ideal method can be used. Serologic tests require specific equipment and are not always available in poverty-stricken zone and are time-consuming. A lateral flow immunoassay (LFIA) may be useful for angiostrongyliasis control. We established a LFIA for the diagnosis of angiostrongyliasis based on 2 monoclonal antibodies (mAbs) against antigens of Angiostrongylus cantonensis adults. The sensitivity and specificity were 91.1% and 100% in LFIA, while those of commercial ELISA kit was 97.8% and 86.3%, respectively. Youden index was 0.91 in LFIA and 0.84 in commercial ELISA kit. LFIA showed detection limit of 1 ng/ml of A. cantonensis ES antigens. This LFIA was simple, rapid, highly sensitive and specific, which opened an alternative approach for the diagnosis of human angiostrongyliasis.

• Structural Engineering and Mechanics
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• v.75 no.4
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• pp.415-424
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• 2020

Recently, many structural damage detection (SDD) methods have been proposed to monitor the safety of structures. As an important modal parameter, mode shape has been widely used in SDD, and the difference of vectors was adopted based on sensitivity analysis and mode shapes in the existing studies. However, amplitudes of mode shapes in different measured points are relative values. Therefore, the difference of mode shapes will be influenced by their amplitudes, and the SDD results may be inaccurate. Focus on this deficiency, a multi-strategy SDD method is proposed based on the included angle of vectors and sparse regularization in this study. Firstly, inspired by modal assurance criterion (MAC), a relationship between mode shapes and changes in damage coefficients is established based on the included angle of vectors. Then, frequencies are introduced for multi-strategy SDD by a weighted coefficient. Meanwhile, sparse regularization is applied to improve the ill-posedness of the SDD problem. As a result, a novel convex optimization problem is proposed for effective SDD. To evaluate the effectiveness of the proposed method, numerical simulations in a planar truss and experimental studies in a six-story aluminum alloy frame in laboratory are conducted. The identified results indicate that the proposed method can effectively reduce the influence of noises, and it has good ability in locating structural damages and quantifying damage degrees.

• Journal of Microbiology and Biotechnology
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• v.23 no.2
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• pp.246-250
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• 2013

In this study, a loop-mediated isothermal amplification (LAMP) method to rapidly detect Staphylococcus aureus strains was developed and evaluated by extensively applying a large number of S. aureus isolates from clinical and food samples. Six primers were specially designed for recognizing eight distinct sequences on the species-specific femA gene of S. aureus. The detection limits were 100 fg DNA/tube and $10^4$ CFU/ml. The LAMP assay was applied to 432 S. aureus strains isolated from 118 clinical and 314 food samples. Total detection rates for the LAMP and polymerase chain reaction assays were 98.4% (306/311) and 89.4% (278/311), respectively.

• Smart Structures and Systems
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• v.29 no.1
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• pp.29-39
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• 2022

Crack detection plays an important role in the maintenance and protection of steel box girder of bridges. However, since the cracks only occupy an extremely small region of the high-resolution images captured from actual conditions, the existing methods cannot deal with this kind of image effectively. To solve this problem, this paper proposed a novel three-stage method based on deep learning technology and morphology operations. The training set and test set used in this paper are composed of 360 images (4928 × 3264 pixels) in steel girder box. The first stage of the proposed model converted high-resolution images into sub-images by using patch-based method and located the region of cracks by CBAM ResNet-50 model. The Recall reaches 0.95 on the test set. The second stage of our method uses the Attention U-Net model to get the accurate geometric edges of cracks based on results in the first stage. The IoU of the segmentation model implemented in this stage attains 0.48. In the third stage of the model, we remove the wrong-predicted isolated points in the predicted results through dilate operation and outlier elimination algorithm. The IoU of test set ascends to 0.70 after this stage. Ablation experiments are conducted to optimize the parameters and further promote the accuracy of the proposed method. The result shows that: (1) the best patch size of sub-images is 1024 × 1024. (2) the CBAM ResNet-50 and the Attention U-Net achieved the best results in the first and the second stage, respectively. (3) Pre-training the model of the first two stages can improve the IoU by 2.9%. In general, our method is of great significance for crack detection.

• Journal of The Korean Astronomical Society
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• v.46 no.5
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• pp.191-200
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• 2013

Full-disk solar images are provided by many solar telescopes around the world. However, the observed images show Non-Radial Variation (NRV) over the disk. In this paper, we propose algorithms for detecting distortions and restoring these images. For detecting NRV, the cross-correlation coefficients matrix of radial profiles is calculated and the minimum value in the matrix is defined as the Index of Non-radial Variation (INV). This index has been utilized to evaluate the H images of GONG, and systemic variations of different instruments are obtained. For obtaining the NRV's image, a Multi-level Morphological Filter (MMF) is designed to eliminate structures produced by solar activities over the solar surface. Comparing with the median filter, the proposed filter is a better choice. The experimental results show that the effect of our automatic detection and restoration methods is significant for getting a flat and high contrast full-disk image. For investigating the effect of our method on solar features, structural similarity (SSIM) index is utilized. The high SSIM indices (close to 1) of solar features show that the details of the structures remain after NRV restoring.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.21
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• pp.9077-9083
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• 2014

Background: This study aimed to summarize the potential diagnostic value of serum DKK1 levels in cancer detection. Materials and Methods: Serum DKK1 was measured using enzyme-linked immunosorbent assay in a case-control study. Then we performed a meta-analysis and the pooled sensitivity, specificity, diagnostic odds ratio, and summary receiver operating characteristic (sROC) curves were used to evaluate the overall test performance. Results: Serum DKK1 levels were found to be significantly upregulated in gastric cancer as compared to controls. ROC curve analysis revealed an AUC of 0.636, indicating the test has the potential to diagnose cancer with poor accuracy. The summary estimates of the pooled sensitivity, specificity and diagnostic odds ratio in meta-analysis were 0.55 with a 95% confidence interval (CI) (0.53-0.57), 0.86 (95%CI, 0.84-0.88) and 12.25 (95%CI, 5.31-28.28), respectively. The area under the sROC was 0.85. Subgroup analysis revealed that the diagnostic accuracy of serum DKK1 in lung cancer (sensitivity: 0.69 with 95%CI, 0.66-0.74; specificity: 0.95 with 95%CI, 0.92-0.97; diagnostic odds ratio: 44.93 with 95%CI, 26.19-77.08) was significantly higher than for any other cancer. Conclusions: Serum DKK1 might be useful as a noninvasive method for confirmation of cancer diagnosis, particularly in the case of lung cancer.

• Bulletin of the Korean Chemical Society
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• v.35 no.10
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• pp.2995-3000
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• 2014

A sensitive concentration method utilising modified gas-purge microsyringe extraction (GP-MSE) was developed. Concentration (reduction in volume) to a microlitre volume was achieved. PAHs were utilised as semivolatile analytes to optimise the various parameters that affect the concentration efficiency. The injection rate and temperature were the key factors that affected the concentration efficiency. An efficient concentration (75.0-96.1%) of PAHs was obtained under the optimised conditions. The method exhibited good reproducibility (RSD values that ranged from 1.5 to 9.0%). The GP-MSE concentration method enhances the volume reduction (concentration factor), leading to a low method detection limit ($0.5-15ngL^{-1}$). Furthermore, this method offers the advantage of small-volume sampling, enabling even the detection of diurnal hourly changes in the concentration of PAHs in ambient air. Utilising this method in combination with GC-MS, the diurnal hourly flux of PAHs from the gas phase of ambient air was measured. Indeed, the proposed technique is a simple, fast, low-cost and environmentally friendly.

• Structural Engineering and Mechanics
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• v.54 no.2
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• pp.221-237
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• 2015

An integrated method is proposed for structural nonlinear damage detection based on time series analysis and the higher statistical moments of structural responses in this study. It combines the time series analysis, the higher statistical moments of AR model residual errors and the fuzzy c-means (FCM) clustering techniques. A few comprehensive damage indexes are developed in the arithmetic and geometric mean of the higher statistical moments, and are classified by using the FCM clustering method to achieve nonlinear damage detection. A series of the measured response data, downloaded from the web site of the Los Alamos National Laboratory (LANL) USA, from a three-storey building structure considering the environmental variety as well as different nonlinear damage cases, are analyzed and used to assess the performance of the new nonlinear damage detection method. The effectiveness and robustness of the new proposed method are finally analyzed and concluded.

• Journal of applied mathematics & informatics
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• v.30 no.5_6
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• pp.847-864
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• 2012

In recent years, using computer networks (wired and wireless networks) has been widespread in many applications. As computer networks become increasingly complex, the accompanied potential threats also grow to be more sophisticated and as such security has become one of the major concerns in them. Prevention methods alone are not sufficient to make them secure; therefore, detection should be added as another defense before an attacker can breach the system. Intrusion Detection Systems (IDSs) have become a key component in ensuring systems and networks security. An IDS monitors network activities in order to detect malicious actions performed by intruders and then initiate the appropriate countermeasures. In this paper, we present a survey and taxonomy of intrusion detection systems and then evaluate and compare them.